README.md

metadata

base_model: runwayml/stable-diffusion-v1-5
library_name: diffusers
license: creativeml-openrail-m
tags:
  - text-to-image
  - dreambooth
  - diffusers-training
  - stable-diffusion
  - stable-diffusion-diffusers
  - text-to-image
  - dreambooth
  - diffusers-training
  - stable-diffusion
  - stable-diffusion-diffusers
inference: true
instance_prompt: a photo of can on the table

DreamBooth - FQiao/output

This is a dreambooth model derived from runwayml/stable-diffusion-v1-5. The weights were trained on a photo of can on the table using DreamBooth. You can find some example images in the following.

DreamBooth for the text encoder was enabled: False.

Intended uses & limitations

How to use

from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained("FQiao/DreamboothCan", torch_dtype=torch.float16).to("cuda")
prompt = "a photo of can on the desk"
image = pipeline(prompt).images[0]
image

Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

Training details

[TODO: describe the data used to train the model]